Quantifying Groundwater Flow and Solute Transport Processes Through Modelling and Experiments

Summary Editorial

Groundwater is a vital source of water for drinking, irrigation, industrial use, and ecosystem maintenance. Climate conditions determine the amount of renewable water resources, but the significant storage potential of aquifers is key for their use in dry areas, when surface water sources are polluted, or when aiming for better water quality. Even if the water stored in aquifers is essential for life and human activities, its study remains challenging due to our inability to see what is underground, in contrast to surface water, where water processes are visible [1]. To explore underground structures, indirect techniques are frequently used, while direct access through the drilling of boreholes remains a noncontinuous and expensive alternative. The challenge of obtaining accurate data on aquifer properties stems from their inherent heterogeneity, with variations occurring over short distances, complicating analysis and interpretation [2]. This challenge is exacerbated when considering the movement of solutes, as the groundwater quality is affected both by natural conditions and human activities at multiple scales. Sources of diffuse pollution such as agriculture or atmospheric deposition or point sources like landfills, airports, mining, and industry can degrade the quality of groundwater and limit its use. Mitigation techniques require detailed knowledge of the processes and contaminant plume distribution to address or prevent future problems.

The quantification of groundwater flow and the study of contamination and solute transport is frequently linked to the development of models to reproduce flow and aquifer conditions. In the context of global change, numerical modelling techniques with a realistic representation of the subsurface are highly relevant, because they allow for the prediction of future conditions under different scenarios. The exponential growth in computer power combined with the increased user-friendliness of groundwater models has facilitated the use of models [3]. However, numerous challenges remain, from input data availability, the integration of different models, uncertainty of obtained results, and the reproducibility and applicability for end-users. In the case of transport simulation, understanding how the specific chemicals and contaminants behave in a certain environment (degraded, adsorbed, etc.) requires detailed knowledge of the aquifer properties, water chemistry, and solid phases.

A conceptual understanding of how a hydrogeological system works is necessary to feed models. Often, this relies on experiments that can range from the field to lab-scale. New and emerging methods for providing additional or novel information are welcomed to complement and improve the current knowledge about aquifer systems when applying groundwater models. Examples of methods for characterizing and monitoring subsurface properties and processes include hydro-geophysics [4,5], improved well logging techniques [6], and field and lab tests [7]. Hence, subsurface heterogeneity can more easily be implemented in standard groundwater modelling software, which together with parameter estimation tools provide more realistic pictures of transport in groundwater systems. Another emerging technique is the analysis of microbes in aquifers, which provides a totally new perspective on the interaction between the realms of geology and biology [8]. The use of temperature as a tracer is now a frequently used tool for understanding hydrogeological functioning, but still, its application in new settings provides additional perspectives and is a complementary source of information for reducing the uncertainties in aquifer knowledge [9].

With all these improvements, are we able to provide better advice to practitioners on how to deal with groundwater and contaminant issues? The range of water and solute travel times from a few months to hundreds of thousands of years reflects different climate conditions and the complex impact of human activities. Identifying the origin and fate of contaminants requires extensive field campaigns that can later be simulated with numerical models. The choice of conceptual model is still one of the most important steps of modelling, leading to the question of how to establish that these initial simplifications are the best. Despite technical advancements in groundwater flow modelling capabilities, the complexity of bio-geochemical reactions often makes it necessary to simplify the flow to a steady-state situation. Moreover, a straightforward task such as revisiting models after some time to assess their accuracy is rarely undertaken. Implementing post-audit models can enhance model design and functionality; however, it is a challenging endeavour that requires updating models that were developed with older methodologies, collecting current data, and securing sufficient time and funding—tasks which are often beyond the scope of typical research projects or contracts.

The need for improved groundwater models, along with the enduring challenges of accessing sufficient data and testing their efficacy, underscores the importance of continuing the development of experimental and alternative methods for researching groundwater systems. While the availability of comprehensive databases and enhanced computational capabilities may obscure the necessity for generating detailed knowledge, the advancement of hydrogeological sciences relies on this continued effort.